Field
The present specification generally relates to computerized analytics.
Technical Background
Globalization, lean operations, outsourcing, supply base complexity, all increase use of outsourcing and unprecedented number of supply chain disruptions. The average cost is estimated between $10M-$50M/year with corresponding damage to future stock returns. Supplier behavior can also damage an organization's corporate brand and shareholder value. Additionally, new laws (e.g., California Supply Chain Transparency Act) require organizations to publicly post how they maintain supply chain visibility. Manually monitoring all the Suppliers (which can number in the thousands for the average Fortune 1000 organization) and their problems is an impossible task. Quarterly financial scores, from an entity such as Dun & Bradstreet, are unlikely to be helpful in such a scenario as well since there wasn't a known financial risk to track. Also, this approach is not sufficient to catch important events in time to mitigate or avoid threats to their supply chain—by the time a quarterly report has run, the damage may be done. Additionally, entities may have Suppliers with multiple manufacturing facilities around the globe. For instance, when a tsunami hits an industry-heavy location, a customer may spend days calling Suppliers to find out who was impacted because they have no way of matching Suppliers to locations.
Current monitoring tools have significant deficiencies including an inability to automatically coordinate events, Suppliers, locations and industries across a corpus of content as well as evaluate/score and surface that content. Therefore, a need exists to collect and analyze data to highlight potential risk scenarios in advance of a situation to avoid possible negative outcomes such as compliance/SOX/monetary failures/losses. These risks may come from unreliable/bad Suppliers (e.g., financial distress, product recalls, ethical issues or simply macro location or industry-based events, such as the Japan tsunami that created massive supply chain disruptions in the computer and auto industries).
In other embodiments, there is a need for a monitoring tool to act as a zeitgeist tracker particularly one that can measure awareness of issues in a specific geographic region as well as across multiple regions or even globally for comparison purposes. Prior art systems and methods might measure the frequency of word terms in a sample set but the results from such analytics are unreliable because a long article, using a keyword with a high frequency, can skew the result. Thus, a system to measure the prevalence of topics based on the number of articles in which certain concepts appear is needed.
Thus, there is a need in the industry for a comprehensive monitoring tool. There is a further need for such a tool focused analysis of supply chain management. Monitoring can come in many forms including focused and comparative consciousness/zeitgeist tracking across geographic regions. Monitoring may also be used to identify areas of opportunity for sales or alternative vendor/Supplier relationships.